How to crop sub-part from national ID without losing quality

Question

I am having a use case where dividing National ID card is mandatory for OCR

Received Image vary in size and pixels number

Samples

Used the following code to crop the ID part

 # Read the input image
img = cv2.imread(imge)

# Convert into grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)


# Convert BGR to HSV
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

# define range of black color in HSV
lower_val = np.array([0,0,0])
upper_val = np.array([179,255,135])

# Threshold the HSV image to get only black colors
mask = cv2.inRange(hsv, lower_val, upper_val)

# invert mask to get black symbols on white background
mask_inv1 = cv2.bitwise_not(mask)

mask_inv = cv2.blur(mask_inv1,(5,5))

image = mask_inv
(h, w) = image.shape[:2]
center = (w / 2, h / 2)

mid_line= int((center[1]+h)/2)
mid_vertical_line = int((center[0]/2)+(0.45*(center[0]/2))) 
ID = image[mid_line:h,mid_vertical_line:w]

Result Image pixelized and blurry, How I can make clean crop without losing quality